High-precision EMG signal decomposition using communication techniques

This paper presents a new approach to the decomposition of electromyographic (EMG) signals. EMG signals consist of a superposition of delayed finite-duration waveforms that carry the information about the firing of different muscle fiber groups. The new approach is based on a communication technical...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2000-09, Vol.48 (9), p.2487-2494
Main Authors: Gut, R., Moschytz, G.S.
Format: Article
Language:English
Subjects:
Accuracy
Applied sciences
Decomposition
Detection, estimation, filtering, equalization, prediction
Electrodes
Electromyography
Exact sciences and technology
Fibers
Firing
Information, signal and communications theory
Mathematical models
Maximum likelihood estimation
Muscles
Needles
Optical fiber communication
Shape
Signal and communications theory
Signal processing
Signal processing algorithms
Signal resolution
Signal, noise
Telecommunications and information theory
Waveforms
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Description
Summary:This paper presents a new approach to the decomposition of electromyographic (EMG) signals. EMG signals consist of a superposition of delayed finite-duration waveforms that carry the information about the firing of different muscle fiber groups. The new approach is based on a communication technical interpretation of the EMG signal. The source is modeled as a signaling system with intersymbol-interference, which encodes a well defined sparse information sequence. This point of view allows a maximum-likelihood (ML) as well as a maximum a posteriori (MAP) estimation of the underlying firing pattern to be made. The high accuracy attainable with the proposed method is illustrated both with measured and artificially generated EMG signals.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.863051